计算机集成制造系统 ›› 2016, Vol. 22 ›› Issue (第1期): 189-201.DOI: 10.13196/j.cims.2016.01.018

• 产品创新开发技术 • 上一篇    下一篇

基于特征语义分析的数控机床设计知识精确智能推送方法

冯毅雄,张舜禹,高一聪+,程锦,谭建荣   

  1. 浙江大学流体动力与机电系统国家重点实验室
  • 出版日期:2016-01-30 发布日期:2016-01-30
  • 基金资助:
    国家自然科学基金资助项目(51322506,51275459);浙江省自然科学基金资助项目(LR14E050003);中央高校基本科研业务费专项资金资助项目(2015FZA4004)。

Intelligent push method of CNC design knowledge based on feature semantic analysis

  • Online:2016-01-30 Published:2016-01-30
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.51322506,51275459),the Natural Science Foundation of Zhejiang Province,China(No.LR14E050003),and the Fundamental Research Funds for the Central Universities,China(No.2015FZA4004).

摘要: 针对设计流程驱动的数控机床设计知识推送过程中不同设计人员在设计任务中的设计知识需求差异问题,提出基于特征语义分析的数控机床设计知识推送方法。通过建立非线性权重的数控机床设计知识描述词—设计知识语义简约矩阵,利用奇异值分解对描述词—设计知识语义简约矩阵进行降维,将描述词—设计知识语义简约矩阵映射至低维特征语义空间。提取了数控机床设计工作流上下文模型中的设计知识需求,并计算了设计知识与知识需求的匹配度,同时构建了设计知识设计人员兴趣个性化的过滤规则对设计知识进行二阶段过滤,最终获得符合设计人员知识需求差异的数控机床设计知识推送方案。以某型号高精度数控坐标镗床切削力设计的设计知识推送方案为例,验证了该方法在工程应用中的正确性与高效性。

关键词: 产品设计, 知识推送, 特征语义, 数控机床, 设计知识

Abstract: Inefficiency of knowledge acquisition has become a key factor restricting of improving the design quality and shortening the design cycle of CNC machine tools.In CNC design knowledge push process driven by design procedure,aiming at the design knowledge demand difference of different designers,an intelligent push method of CNC design knowledge based on latent semantic analysis was proposed.A semantic matrix of description words and design knowledge with nonlinear weight coefficient was developed,and the semantic matrix was mapped to a low-dimensional space by singular value decomposition.The requirements of design knowledge were extracted from the model of design process and the fitness value was evaluated.According to the designers'personal interests,the filtering rules were created and the push solution of design knowledge was filtered.A case study was provided to illustrate the practical application of the proposed method.

Key words: product design, knowledge push, feature semantic, machine tools, design knowledge

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